Evidence map›Paper›PMID 34539226›Full record

ArticleInformation systems frontiers : a journal of research and innovation2021

The Application of the Principles of Responsible AI on Social Media Marketing for Digital Health.

Rui Liu, Suraksha Gupta, Parth Patel

Abstract read
In one paragraph

Article in Information systems frontiers : a journal of research and innovation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. User Privacy, Surveillance and Public Health during COVID-19 - An Examination of Twitterverse.Information systems frontiers : a journal of research and innovation · 2022
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Rui LiuNewcastle University Business School, Newcastle University, 5 Barrack Road, Newcastle upon Tyne, NE14SE Tyne and Wear UK.ORCID 0000-0003-2080-7218
Suraksha GuptaNewcastle University Business School, Newcastle University, 5 Barrack Road, Newcastle upon Tyne, NE14SE Tyne and Wear UK.
Parth PatelDiscipline of Management & Human Resources, Australian Institute of Business, 1 King William Street, Adelaide, 5000 South Australia Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Social media enables medical professionals and authorities to share, disseminate, monitor, and manage health-related information digitally through online communities such as Twitter and Facebook. Simultaneously, artificial intelligence (AI) powered social media offers digital capabilities for organizations to select, screen, detect and predict problems with possible solutions through digital health data. Both the patients and healthcare professionals have benefited from such improvements. However, arising ethical concerns related to the use of AI raised by stakeholders need scrutiny which could help organizations obtain trust, minimize privacy invasion, and eventually facilitate the responsible success of AI-enabled social media operations. This paper examines the impact of responsible AI on businesses using insights from analysis of 25 in-depth interviews of health care professionals. The exploratory analysis conducted revealed that abiding by the responsible AI principles can allow healthcare businesses to better take advantage of the improved effectiveness of their social media marketing initiatives with their users. The analysis is further used to offer research propositions and conclusions, and the contributions and limitations of the study have been discussed.

Indexed as

Consumer trust theoryDigital healthInformation sharing theoryResponsible AISocial media marketingTechnology acceptance model

Identifiers

PMID34539226
PMCPMC8435400

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.